Business intelligence

Analysis of companies, products, and user strategies in the area of business intelligence. Related subjects include:

October 31, 2013

Specialized business intelligence

A remarkable number of vendors are involved in what might be called “specialized business intelligence”. Some don’t want to call it that, because they think that “BI” is old and passé’, and what they do is new and better. Still, if we define BI technology as, more or less:

then BI is indeed a big part of what they’re doing.

Why would vendors want to specialize their BI technology? The main reason would be to suit it for situations in which even the best general-purpose BI options aren’t good enough. The obvious scenarios are those in which the mismatch is one or both of:

For example, in no particular order: Read more

October 30, 2013

Splunk strengthens its stack

I’m a little shaky on embargo details — but I do know what was in my own quote in a Splunk press release that went out yesterday. :)

Splunk has been rolling out a lot of news. In particular:

I imagine there are some operationally-oriented use cases for which Splunk instantly offers the best Hadoop business intelligence choice available. But what I really think is cool is Splunk’s schema-on-need story, wherein:

That highlights a pretty serious and flexible vertical analytic stack. I like it.

October 30, 2013

Glassbeam instantiates a lot of trends

Glassbeam checked in recently, and they turn out to exemplify quite a few of the themes I’ve been writing about. For starters:

Glassbeam basics include:

All Glassbeam customers except one are SaaS/cloud (Software as a Service), and even that one was only offered a subscription (as oppose to perpetual license) price.

So what does Glassbeam’s technology do? Glassbeam says it is focused on “machine data analytics,” specifically for the “Internet of Things”, which it distinguishes from IT logs.* Specifically, Glassbeam sells to manufacturers of complex devices — IT (most of its sales so far ), medical, automotive (aspirational to date), etc. — and helps them analyze “phone home” data, for both support/customer service and marketing kinds of use cases. As of a recent release, the Glassbeam stack can: Read more

October 18, 2013

Entity-centric event series analytics

Much of modern analytic technology deals with what might be called an entity-centric sequence of events. For example:

Analytic questions are asked along the lines “Which sequences of events are most productive in terms of leading to the events we really desire?”, such as product sales. Another major area is sessionization, along with data preparation tasks that boil down to arranging data into meaningful event sequences in the first place.

A number of my clients are focused on such scenarios, including WibiData, Teradata Aster (e.g. via nPath), Platfora (in the imminent Platfora 3), and others. And so I get involved in naming exercises. The term entity-centric came along a while ago, because “user-centric” is too limiting. (E.g., the data may not be about a person, but rather specifically about the actions taken on her mobile device.) Now I’m adding the term event series to cover the whole scenario, rather than the “event sequence(s)” I might appear to have been hinting at above.

I decided on “event series” earlier this week, after noting that:  Read more

October 10, 2013

Aster 6, graph analytics, and BSP

Teradata Aster 6 has been preannounced (beta in Q4, general release in Q1 2014). The general architectural idea is:

There’s much more, of course, but those are the essential pieces.

Just to be clear: Teradata Aster 6, aka the Teradata Aster Discovery Platform, includes HDFS compatibility, native MapReduce and ways of invoking Hadoop MapReduce on non-Aster nodes or clusters — but even so, you can’t run Hadoop MapReduce within Aster over Aster’s version of HDFS.

The most dramatic immediate additions are in the graph analytics area.* The new SQL-Graph is supported by something called BSP (Bulk Synchronous Parallel). I’ll start by observing (and some of this is confusing):

Use cases suggested are a lot of marketing, plus anti-fraud.

*Pay no attention to Aster’s previous claims to do a good job on graph — and not only via nPath — in SQL-MR.

So far as I can infer from examples I’ve seen, the semantics of Teradata Aster SQL-Graph start:

Within those functions, the core idea is:  Read more

October 6, 2013

What matters in investigative analytics?

In a general pontification on positioning, I wrote:

every product in a category is positioned along the same set of attributes,

and went on to suggest that summary attributes were more important than picky detailed ones. So how does that play out for investigative analytics?

First, summary attributes that matter for almost any kind of enterprise software include:

*I picked up that phrase when — abbreviated as RAS — it was used to characterize the emphasis for Oracle 8. I like it better than a general and ambiguous concept of “enterprise-ready”.

The reason I’m writing this post, however, is to call out two summary attributes of special importance in investigative analytics — which regrettably which often conflict with each other — namely:

Much of what I work on boils down to those two subjects. For example: Read more

September 29, 2013

Visualization or navigation?

I’ve suggested in the past, approximately, that the platform technology side of business intelligence is more significant than the user interface. That formulation, however, doesn’t exactly capture what I believe. To be more precise, let’s differentiate between a couple aspects of business intelligence UI.

It might seem that a lot of the action in business intelligence revolves around ever-better visualization. After all, Tableau is clearly identified as a visualization-centric technology; who’s hotter than Tableau? And numerous other vendors talk of “visualizations” too. But I don’t think that’s exactly right — rather, I see navigation as being a much bigger deal. And unlike most pure visualization, navigation usually depends strongly on underlying platform capabilities.

Examples of what I mean by innovative navigation — all of which have been developed or have gained prominence over the past decade or so — include:

Read more

August 14, 2013

The two sides of BI

As is the case for most important categories of technology, discussions of BI can get confused. I’ve remarked in the past that there are numerous kinds of BI, and that the very origin of the term “business intelligence” can’t even be pinned down to the nearest century. But the most fundamental confusion of all is that business intelligence technology really is two different things, which in simplest terms may be categorized as user interface (UI) and platform* technology. And so:

*I wanted to say “server” or “server-side” instead of “platform”, as I dislike the latter word. But it’s too inaccurate, for example in the case of the original Cognos PowerPlay, and also in various thin-client scenarios.

Key aspects of BI platform technology can include:

Read more

August 12, 2013

Things I keep needing to say

Some subjects just keep coming up. And so I keep saying things like:

Most generalizations about “Big Data” are false. “Big Data” is a horrific catch-all term, with many different meanings.

Most generalizations about Hadoop are false. Reasons include:

Hadoop won’t soon replace relational data warehouses, if indeed it ever does. SQL-on-Hadoop is still very immature. And you can’t replace data warehouses unless you have the power of SQL.

Note: SQL isn’t the only way to provide “the power of SQL”, but alternative approaches are just as immature.

Most generalizations about NoSQL are false. Different NoSQL products are … different. It’s not even accurate to say that all NoSQL systems lack SQL interfaces. (For example, SQL-on-Hadoop often includes SQL-on-HBase.)

Read more

August 8, 2013

Curt Monash on video

I made a remarkably rumpled video appearance yesterday with SiliconAngle honchos John Furrier and Dave Vellante. (Excuses include <3 hours sleep, and then a scrambling reaction to a schedule change.) Topics covered included, with approximate timechecks:

Edit: Some of my remarks were transcribed.

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